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Academic Journal of Computing & Information Science, 2024, 7(2); doi: 10.25236/AJCIS.2024.070212.

Optimization of robot path planning based on improved BP algorithm


Biao Chen1, Shan Hu1,2, Tianzhi Zhang1

Corresponding Author:
Shan Hu

1School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, China

2Tianjin Key Laboratory of Information Sensing & Intelligent Control, Tianjin, China


Path planning is one of the key problems of welding robots. In the face of increasing accuracy and efficiency requirements in the manufacturing industry, the importance of robot path planning has also increased. For welding robots, short welding time and stable welding process are generally required. In this paper, genetic algorithm is used to optimize BP neural network algorithm, so as to obtain better weights and thresholds, so as to obtain better solutions in path planning. After simulation and verification in MATLAB, the results show that, the optimized BP neural network algorithm effectively improves the efficiency of the algorithm and optimizes the ability of finding the global optimal path.


Improved BP neural network algorithm; Welding robot; Path planning; Genetic algorithm

Cite This Paper

Biao Chen, Shan Hu, Tianzhi Zhang. Optimization of robot path planning based on improved BP algorithm. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 2: 85-90. https://doi.org/10.25236/AJCIS.2024.070212.


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